Job description

Duration: 12 months Summary: Seeking an Aerospace Engineer to act as a domain expert supporting our AI Research initiatives. In this role, you will bridge the gap between traditional aerospace engineering and artificial intelligence by helping our team develop, validate, and stress-test AI tools tailored for aerospace systems, flight dynamics, and structural analysis. You will partner closely with AI researchers to evaluate engineering workflows, define benchmarks, and ensure AI outputs meet the rigorous standards of the discipline. Job Responsibilities: • Validate AI Workflows: Evaluate the feasibility, safety, and practical utility of AI-generated aerospace designs, mission profiles, and complex simulations. • Define Tasks & Benchmarks: Help design, collect, and validate the specific engineering tasks, edge cases, and evaluation metrics (validators) that our AI models need to master. • Provide Domain Expertise: Operate comfortably across a wide range of aerospace sub-disciplines, applying generalist knowledge in aerodynamics, propulsion, orbital mechanics, and avionics (GNC) to assess model performance. • Collaborate Cross-Functionally: Partner directly with AI researchers and cross-functional stakeholders to translate complex aerospace constraints into clear, actionable feedback for model training. • Ensure Compliance: Ensure all evaluated deliverables and AI-generated outputs follow applicable aerospace engineering standards, safety requirements, and documented processes. Skills: • Power-user proficiency with industry-standard aerospace design and simulation tools (e.g., STK, NASTRAN/PATRAN, ANSYS Fluent, OpenVSP, or MATLAB/Simulink). • Broad foundational knowledge across aerospace sub-fields (aerodynamics, propulsion, orbital mechanics, avionics). • Experience working in cross-functional environments and communicating technical engineering information clearly to non-domain audiences (e.g., software engineers, AI scientists). • Ability to manage multiple tasks and meet deadlines in a fast-paced environment. • Basic scripting skills (e.g., Python, MATLAB) to help parse data or interface with AI environments. (Note: Advanced software engineering or machine learning expertise is not required). Education/Experience: • 3-5 years of practical, post-graduation aerospace engineering experience. • Bachelor’s degree in Aerospace Engineering or related engineering field, or equivalent practical experience. Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation. About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com . US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. AI Statement: By applying, you acknowledge that AI-assisted tools may be used during hiring.

Requirements

Must-haves

Duration: 12 months
Validate AI Workflows: Evaluate the feasibility, safety, and practical utility of AI-generated aerospace designs, mission profiles, and complex simulations.
Define Tasks & Benchmarks: Help design, collect, and validate the specific engineering tasks, edge cases, and evaluation metrics (validators) that our AI models need to master.
Collaborate Cross-Functionally: Partner directly with AI researchers and cross-functional stakeholders to translate complex aerospace constraints into clear, actionable feedback for model training.
Ensure Compliance: Ensure all evaluated deliverables and AI-generated outputs follow applicable aerospace engineering standards, safety requirements, and documented processes.
Power-user proficiency with industry-standard aerospace design and simulation tools (e.g., STK, NASTRAN/PATRAN, ANSYS Fluent, OpenVSP, or MATLAB/Simulink).
Broad foundational knowledge across aerospace sub-fields (aerodynamics, propulsion, orbital mechanics, avionics).
Experience working in cross-functional environments and communicating technical engineering information clearly to non-domain audiences (e.g., software engineers, AI scientists).
Ability to manage multiple tasks and meet deadlines in a fast-paced environment.
Basic scripting skills (e.g., Python, MATLAB) to help parse data or interface with AI environments. (Note: Advanced software engineering or machine learning expertise is not required).
3-5 years of practical, post-graduation aerospace engineering experience.
Bachelor’s degree in Aerospace Engineering or related engineering field, or equivalent practical experience.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythonmachine learning

Platform: jobdiva
Effort: medium